AWS Announces Availability of P2 Instances for Amazon EC2

New GPU instance type offers the most processing power available in
the cloud for artificial intelligence, high-performance computing and
big data processing

New Amazon Machine Image (AMI) comes pre-installed withframeworks
that help customers reduce model training time from weeks to hours

September 30, 2016 02:35 AM Eastern Time

SEATTLE--(EON: Enhanced Online News)--Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ:AMZN),
today announced the availability of P2 instances, a new GPU instance
type for Amazon Elastic Compute Cloud (Amazon EC2) designed for
compute-intensive applications that require massive parallel floating
point performance, including artificial intelligence, computational
fluid dynamics, computational finance, seismic analysis, molecular
modeling, genomics, and rendering. With up to 16 NVIDIA Tesla K80 GPUs,
P2 instances are the most powerful GPU instances available in the cloud.
To get started with P2 instances, visit http://aws.amazon.com/ec2/instance-types/p2/.

“Deep learning plays a central role
in our image and video classification APIs, and high performance GPUs in
the AWS Cloud can vastly accelerate inference for our algorithms”

P2 instances allow customers to build and deploy compute-intensive
applications using the CUDA parallel computing platform or the OpenCL
framework without up-front capital investments. To offer the best
performance for these high performance computing applications, the
largest P2 instance offers 16 GPUs with a combined 192 Gigabytes (GB) of
video memory, 40,000 parallel processing cores, 70 teraflops of single
precision floating point performance, over 23 teraflops of double
precision floating point performance, and GPUDirect technology for
higher bandwidth and lower latency peer-to-peer communication between
GPUs. P2 instances also feature up to 732 GB of host memory, up to 64
vCPUs using custom Intel Xeon E5-2686 v4 (Broadwell) processors,
dedicated network capacity for I/O operation, and enhanced networking
through the Amazon EC2 Elastic Network Adaptor.

“Two years ago, we launched G2 instances to support customers running
graphics and compute-intensive applications,” said Matt Garman, Vice
President, Amazon EC2. “Today, as customers embrace heavier GPU compute
workloads such as artificial intelligence, high-performance computing,
and big data processing, they need even higher GPU performance than what
was previously available. P2 instances offer seven times the
computational capacity for single precision floating point calculations
and 60 times more for double precision floating point calculations than
the largest G2 instance, providing the best performance for
compute-intensive workloads such as financial simulations, energy
exploration and scientific computing.”

Clarifai provides image and video recognition APIs for some of the
world’s most innovative companies. “Deep learning plays a central role
in our image and video classification APIs, and high performance GPUs in
the AWS Cloud can vastly accelerate inference for our algorithms,” said
Matthew Zeiler, CEO, Clarifai. “Amazon EC2 P2 instances will give us the
agility to scale up to serving numerous models in parallel, delivering
results faster than previously possible without massive capital
expenditures, un-utilized hardware, and large data transfers. We will be
able to leverage the massive aggregate single precision floating point
processing capability of Amazon EC2 P2 instances to reduce inference
times for our customers, and substantially reduce the cost of
processing.”

Altair Engineering empowers innovation and decision-making through
technology that optimizes the analysis, management, and visualization of
business and engineering information. “Simulation technology is at the
core of Altair’s business and with our GPU solver partner FluiDyna GmbH,
we’ve made significant investments in domain decomposition to optimize
our computational fluid dynamics (CFD) software, nanoFluidX, for
multi-GPU scaling for increased performance and reduced cost,” said
Stephen Cosgrove, Director of CFD, Altair. “We’re able to leverage the
massive amount of aggregate GPU memory and double precision floating
point performance in Amazon EC2 P2 instances to fit more simulations
into a single node, significantly reduce customer simulation times, and
reduce the cost of running large simulations.”

MathWorks, the leading developer of mathematical computing software,
helps millions of engineers, scientists, researchers, and students
around the world analyze and design systems and products that are
transforming the world. “MATLAB users moving their analytics and
simulation workloads onto the AWS Cloud require their analyses to be
processed quickly,” said Silvina Grad-Freilich, Senior Product Manager,
MathWorks. “The massive parallel floating point performance of Amazon
EC2 P2 instances, combined with up to 64 vCPUs and 732 GB host memory,
will enable customers to realize results faster and process larger
datasets than was previously possible.”

MapD is a GPU database for interactive SQL querying and visualization of
multi-billion record datasets. “As the leader in GPU-powered databases
and visual analytics applications, we are deeply invested in the
emergence of large, cloud-based GPU instances and P2 is the most
powerful we have seen,” said Todd Mostak, CEO and Founder, MapD. “Our
performance on Amazon EC2 P2 instances is exceptional. On a
dollar-to-dollar basis across a set of standard SQL benchmarks, MapD is
78 times faster on Amazon EC2 P2 instances than CPU-based solutions.
Furthermore, these speedups were seen over multi-billion row datasets,
speaking directly to our ability to deliver performance at scale with
these instances. With this launch, our customers can now query and
visualize billions of rows of data within milliseconds while enjoying
the flexibility, scalability and reliability they have come to expect
from AWS.”

Sonus delivers intelligent and secure, cloud optimized solutions for
real time communications used by the world's leading service providers
and enterprises. “Real time communications are rapidly evolving, and
they require transcoding between formats for use on multiple devices,”
said Mykola Konrad, Vice President, Product Management and Marketing,
Sonus. “GPUs are becoming more of a disruptor for transcoding services
and they offer a cost effective solution for scaling our Session Border
Controller application in the cloud. Because of our collaboration with
AWS, Sonus has developed the industry’s first GPU optimized session
border controller by leveraging the GPU parallel computing power and
Enhanced Networking of Amazon EC2 P2 instances, which decreases network
costs for our customers.”

Customers can launch P2 instances using the AWS Management Console, AWS
Command Line Interface (CLI), AWS SDKs, and third-party libraries. P2
instances are available in three instance sizes: p2.16xlarge with 16
GPUs, p2.8xlarge with 8 GPUs, and p2.xlarge with 1 GPU. P2 instances are
available in the US East (N. Virginia), US West (Oregon), and EU
(Ireland) Regions.

Amazon Machine Images (AMIs) from AWS, NVIDIA, and other sellers are
available in the AWS Marketplace to help customers get started within
minutes. The AWS Deep Learning AMI comes preinstalled with MXNet and
Caffe deep learning frameworks to enable customers to reduce model
training time from weeks to hours. It also lets them experiment with
artificial intelligence without making large upfront capital
expenditures. The AMI from NVIDIA includes pre-installed drivers and the
CUDA toolkit. It’s designed for developers working on a range of
GPU-intensive workloads.

About Amazon Web Services

For 10 years, Amazon Web Services has been the world’s most
comprehensive and broadly adopted cloud platform. AWS offers over 70
fully featured services for compute, storage, databases, analytics,
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India. AWS services are trusted by more than a million active customers
around the world -- including the fastest growing startups, largest
enterprises, and leading government agencies -- to power their
infrastructure, make them more agile, and lower costs. To learn more
about AWS, visit http://aws.amazon.com.

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